An unmanned aerial vehicle image radiation consistency correction method under varying illumination conditions

Abstract

The present application relates to a kind of unmanned aerial vehicle image radiation consistency correction method under varying illumination conditions, comprising: obtaining the orthographic image of target farmland area;Orthographic image of target farmland area is positioned and corrected in space, and the spatial position of each farmland plot or test plot in orthographic image in target farmland area is obtained;According to the spatial position of each farmland plot or test plot in orthographic image, orthographic image is cut, and the radiation information affected by illumination change in cut image is corrected in radiation consistency;Based on the image data after radiation consistency correction, crop growth monitoring, farmland condition evaluation, variety comparison analysis or yield prediction are carried out.The present application can be widely applied to the field of remote sensing image processing and spectral correction.

Description

A method for radiometric consistency correction of UAV images under varying illumination conditions Technical Field

[0001] This invention relates to the field of remote sensing image processing and spectral correction, specifically to a method for radiometric consistency correction of UAV images under varying illumination conditions, applicable to data correction and quantitative inversion scenarios of UAV low-altitude remote sensing, aerial remote sensing, and ground spectral measurements. Background Technology

[0002] During the acquisition of optical remote sensing data, atmospheric conditions and illumination conditions change rapidly over time, and conventional absolute reflectance correction methods based on irradiance (such as the CRP method using a standard reflectance correction plate) are prone to failure in cloudy or unstable weather.

[0003] This is because conventional methods are generally based on the following assumption: the correction plate and the target ground object receive the same irradiance in all bands, i.e. However, this assumption often fails when thin clouds, aerosols, or changes in illumination angle are present, leading to inaccurate reflectance correction and consequently affecting the accuracy of vegetation index calculations and quantitative remote sensing inversion. Therefore, a new correction method is needed to mitigate the impact of atmospheric and illumination instabilities on the results and achieve more robust reflectance acquisition.

[0004] In addition, among existing UAV image radiometric correction methods, the most widely used method is alternative calibration, which uses one or more reference panels to convert digital values ​​into reflectance, i.e., the PanelCal method, a radiometric correction technique based on ground reflectance calibration boards. This method typically relies on deploying standard reflectance calibration boards within the flight area and assuming relatively stable lighting conditions during flight, performing overall radiometric correction on the image using the reflectance calibration boards. However, in practical applications, especially during large-scale farmland flights or multiple flights, cloud cover, changes in solar altitude angle, and uneven local illumination often occur, leading to significant radiometric inconsistencies in data acquired from different areas or at different times in the image, thus affecting the accuracy and stability of reflectance calculations. Summary of the Invention

[0005] To address the problem of correction failure caused by changes in irradiance under variable weather conditions, the present invention aims to provide a method for correcting the radiometric consistency of UAV images under varying illumination conditions. This method can effectively characterize and compensate for radiometric differences in images caused by changes in illumination without relying on a single calibration board or a stable illumination assumption.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A method for radiometric consistency correction of UAV images under varying illumination conditions includes:

[0008] Obtain orthophotos of the target farmland area;

[0009] Spatial positioning correction is performed on the orthophoto of the target farmland area, and the spatial location of each farmland plot or test plot in the orthophoto is obtained.

[0010] Orthophotos are cropped based on the spatial location of each farmland plot or experimental plot in the orthophoto, and radiometric consistency correction is performed on the radiometric information in the cropped images affected by changes in illumination based on the constant ratio assumption.

[0011] Based on the radiometrically corrected image data, crop growth monitoring, crop condition assessment, variety comparison analysis, or yield prediction can be carried out.

[0012] Furthermore, acquiring the orthophoto of the target farmland area includes:

[0013] Using drones equipped with multispectral or visible light sensors, aerial imaging of target farmland areas is carried out under natural lighting conditions;

[0014] Multiple UAV images were stitched together to generate an orthophoto covering the target farmland area.

[0015] Furthermore, the step of performing spatial positioning correction on the orthophoto of the target farmland area and obtaining the spatial location of each farmland plot or test plot in the orthophoto within the target farmland area includes:

[0016] By combining real-time dynamic differential positioning technology, spatial positioning correction is performed on the orthophoto of the target farmland area to obtain accurate geographic coordinate information of each pixel in the orthophoto.

[0017] Based on the accurate geographic coordinates of each pixel, the spatial location of each farmland plot or experimental plot in the orthophoto is determined by using the vector boundary coordinates of each farmland plot or experimental plot obtained in advance.

[0018] Furthermore, the step of cropping the orthophoto image based on the spatial location of each farmland plot or test area in the orthophoto image, and performing radiometric consistency correction on the radiometric information in the cropped image affected by illumination changes based on the constant scaling assumption, includes:

[0019] Based on the spatial location of each farmland plot or experimental plot in the orthophoto, the orthophoto is cropped to obtain a cropped silhouette image corresponding to each farmland plot or experimental plot;

[0020] For the cropped images of each farmland plot or experimental plot obtained by cropping, based on the assumption of constant proportion, the radiation information in the cropped images affected by changes in illumination is subjected to radiation consistency correction processing.

[0021] Furthermore, based on the assumption of a constant ratio, the cut-out images of each farmland plot or test area are subjected to radiometric consistency correction processing on the radiometric information affected by changes in illumination, including:

[0022] Calculate the constant coefficient of irradiance ratio based on the silhouette images of each farmland plot or experimental area;

[0023] Calculate the absolute reflectance of the target ground object based on the constant irradiance ratio coefficient;

[0024] The absolute reflectance of the target object is normalized to obtain the relative reflectance of the target object.

[0025] Furthermore, the constant coefficient of irradiance ratio is calculated based on the silhouette images of each farmland plot or experimental area. The calculation formula is as follows:

[0026]

[0027] In the formula, Indicates the radiation calibration factor; , These represent the center wavelengths of different wavebands; and Indicates the calibration plate at wavelength and wavelength The amount of radiation at that location; and These represent the target ground features at wavelengths of [wavelength values ​​missing]. and wavelength The amount of radiation at that location.

[0028] Furthermore, the formula for calculating the absolute reflectance of the target feature is as follows:

[0029]

[0030] In the formula, Indicates the target ground features at wavelength Absolute reflectance at that location; Indicates the target ground features at wavelength Radiance at that location; Indicates the target ground features at wavelength The amount of radiation at that location; Indicates the calibration plate at wavelength Radiance at that location; Indicates the calibration plate at wavelength The amount of radiation at that location; Indicates the calibration plate at wavelength The known reflectivity at that location; This represents the radiation calibration coefficient.

[0031] Furthermore, the formula for calculating the relative reflectance of the target feature is as follows:

[0032]

[0033] In the formula: Indicates the target ground features at wavelength Relative reflectance at; Indicates the target ground features at wavelength Absolute reflectance at that location; Indicates the normalized baseline value; Indicates the target ground features at wavelength Radiance at that location; Indicates the calibration plate at wavelength Radiance at that location, This represents the cross-band normalization term.

[0034] The present invention, by adopting the above technical solutions, has the following advantages: It can effectively correct radiation deviations caused by inconsistent illumination, resulting in higher consistency and stability of image data acquired between different cells in a single flight and across multiple flights, thereby significantly enhancing the application value of UAV imagery in crop phenotypic monitoring at the cell scale. The method of this invention is not dependent on any specific crop type and is applicable to field remote sensing monitoring scenarios for various crops, demonstrating good versatility and promising prospects for widespread application.

[0035] Therefore, this invention can be widely applied in the fields of remote sensing image processing and spectral correction. Attached Figure Description

[0036] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. In the drawings:

[0037] Figure 1 is a flowchart of the UAV image radiometric consistency correction method under varying illumination conditions provided in an embodiment of the present invention.

[0038] Figure 2 is a GAI inversion diagram obtained by the correction method of the present invention under cloudy conditions, provided by an embodiment of the present invention.

[0039] Figure 3 is a GAI inversion diagram obtained by the radiation correction method (PanelCal) based on the ground reflectivity calibration plate under cloudy conditions provided by the embodiment of the present invention;

[0040] Figure 4 is a graph showing the change of radiation calibration coefficient over time under clear weather conditions provided in the embodiment of the present invention.

[0041] Figure 5 is a graph showing the change of radiation calibration coefficient over time under cloudy weather conditions provided in the embodiment of the present invention.

[0042] Figure 6 is a graph showing the change of radiation calibration coefficient over time under cloudy weather conditions provided in an embodiment of the present invention. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention are within the scope of protection of the present invention.

[0044] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0045] Unmanned aerial vehicle (UAV) remote sensing technology is commonly used in field crop phenotypic monitoring to acquire high-resolution image data of crops within a specific area. However, due to the instability of lighting conditions in the natural environment, such as changes in cloud cover, solar altitude angle, and local shading, images acquired at different times or locations during the same flight may still exhibit significant radiation deviations. Consequently, the pixel values ​​in the images may not accurately reflect the actual reflectance characteristics of the crops.

[0046] To improve the reliability of UAV imagery in quantitative analysis, reflectance correction is necessary for the original images. The purpose of reflectance correction is to eliminate or reduce the influence of illumination variations on the image's radiation information, enabling the corrected image data to more realistically and accurately represent the crop's ability to reflect incident radiation energy. After correction, the values ​​of each pixel in the resulting image no longer merely represent the raw digital values ​​received by the sensor, but rather reflectance data with clear physical meaning related to the actual reflectance characteristics of the crop.

[0047] In some embodiments of the present invention, a method for radiometric consistency correction of UAV images under varying illumination conditions is provided. First, the images acquired by the UAV are stitched and spatially located, and the image regions corresponding to each farmland plot or experimental plot are extracted according to the field trial design. Then, the cropped farmland plot or experimental plot image data are subjected to UAV image radiometric consistency correction under varying illumination conditions to obtain corrected reflectance images or reflectance datasets. This invention can eliminate the influence of illumination instability on quantitative reflectance calculation, improving the applicability of remote sensing images under complex weather conditions. For example, it is applicable to agricultural remote sensing monitoring fields such as vegetation index (NDVI, EVI, etc.) calculation, crop classification, pest and disease monitoring, and soil parameter inversion, and is particularly suitable for high-precision quantitative reflectance acquisition at the farmland plot scale.

[0048] Example 1

[0049] As shown in Figure 1, the present invention provides a method for radiometric consistency correction of UAV images under varying illumination conditions, which includes the following steps:

[0050] 1) Obtain orthophotos of the target farmland area.

[0051] Specifically, it includes the following steps:

[0052] 1.1) Use drones equipped with multispectral or visible light sensors to conduct aerial imaging of the target farmland area under natural lighting conditions;

[0053] In this embodiment, when using a drone for aerial imaging, complex lighting conditions such as changes in cloud cover and fluctuations in light intensity are allowed during the flight, without the need for strict lighting consistency restrictions during the flight period.

[0054] 1.2) Perform image stitching on the acquired UAV images to generate an orthophoto covering the target farmland area.

[0055] 2) Perform spatial positioning correction on the orthophoto of the target farmland area and obtain the spatial location of each farmland plot or test plot in the orthophoto within the target farmland area.

[0056] Specifically, it includes the following steps:

[0057] 2.1) Combine real-time dynamic differential positioning (RTK) technology to perform high-precision spatial positioning correction on the orthophoto of the target farmland area in order to obtain accurate geographic coordinate information of each pixel in the orthophoto.

[0058] 2.2) Based on the accurate geographic coordinate information of each pixel, the spatial location of each farmland plot or experimental plot in the orthophoto is determined by using the vector boundary coordinates of each farmland plot or experimental plot obtained in advance.

[0059] 3) Based on the spatial location of each farmland plot or experimental plot in the orthophoto, the orthophoto is cropped, and the radiometric consistency correction is performed on the radiometric information in the cropped image affected by changes in illumination based on the constant ratio assumption.

[0060] Specifically, it includes the following steps:

[0061] 3.1) Based on the spatial location of each farmland plot or experimental plot in the orthophoto, the orthophoto is cropped to obtain a cropped silhouette image corresponding to each farmland plot or experimental plot;

[0062] 3.2) For the cropped images of each farmland plot or experimental plot obtained by cropping, based on the constant ratio assumption, the radiation information in the cropped images affected by changes in illumination is subjected to radiation consistency correction processing.

[0063] In this embodiment, radiation conformity correction includes:

[0064] 3.2.1) Calculate the constant coefficient of irradiance ratio based on the silhouette images of each farmland plot or experimental area.

[0065] In this embodiment, it is assumed that the irradiance ratio between the calibration plate and the target ground object remains constant across all spectral bands. The constant irradiance ratio coefficient is then calculated using the following formula:

[0066]

[0067] In the formula, Indicates the radiation calibration factor; , These represent the center wavelengths of different wavebands; and Indicates the calibration plate at wavelength and wavelength The amount of radiation at that location; and These represent the target ground features at wavelengths of [wavelength values ​​missing]. and wavelength The amount of radiation at that location.

[0068] 3.2.2) Calculate the absolute reflectance of the target ground object based on the constant irradiance ratio coefficient.

[0069] The formula for calculating the absolute reflectance of the target object is as follows:

[0070]

[0071] In the formula, Indicates the target ground features at wavelength Absolute reflectance at that location; Indicates the target ground features at wavelength Radiance at that location; Indicates the target ground features at wavelength The amount of radiation at that location; Indicates the calibration plate at wavelength Radiance at that location; Indicates the calibration plate at wavelength The amount of radiation at that location; Indicates the calibration plate at wavelength The known reflectivity at that location; This represents the radiation calibration coefficient.

[0072] 3.2.3) Normalize the absolute reflectance of the target object to obtain the relative reflectance of the target object.

[0073] First, calculate the normalized baseline value:

[0074]

[0075] Secondly, based on the normalized baseline value and the absolute reflectance of the target surface, the relative reflectance is calculated using the following formula:

[0076]

[0077] In the formula: Indicates the target ground features at wavelength The relative reflectance at that location; Indicates the target ground features at wavelength Absolute reflectance at that location; Indicates the normalized baseline value; Indicates the target ground features at wavelength Radiance at that location; Indicates the calibration plate at wavelength Radiance at that location, This represents the cross-band normalization term.

[0078] In this embodiment, by using radiometric consistency correction, radiometric inconsistencies caused by different shooting times, different lighting conditions, and image stitching can be eliminated or reduced, so that the pixel values ​​of each field plot image can accurately reflect the true reflectance characteristics of the ground objects, thereby obtaining stable and comparable reflectance data.

[0079] 4) Based on the image data after radiometric consistency correction, crop growth monitoring, crop condition assessment, variety comparison analysis, and yield prediction are carried out.

[0080] In this embodiment, after radiation consistency correction, the obtained reflectance data can be directly used for the extraction and analysis of crop field phenotypic parameters, such as reflectance differences, temporal variation characteristics, and spatial distribution characteristics between different plots. This provides a reliable data foundation for crop growth status assessment, varietal difference analysis, and agronomic trait comparison. Especially under field plot experimental conditions, due to the small area and dense distribution of each experimental plot, the spatial and temporal variations in light conditions are more significant, making it difficult for traditional methods to guarantee the consistency and comparability of data between different plots.

[0081] Example 2

[0082] In this embodiment, the method of the present invention and the PanelCal method are applied to the same batch of UAV image data, and reflectance calculation and comparative analysis are performed at the same field plot scale.

[0083] As shown in Figures 2 and 3, under cloudy conditions, the images corrected using the conventional PanelCal method still exhibit significant reflectance fluctuations between different field plots. However, the GAI inversion images obtained using the method of this invention maintain high accuracy even under cloudy conditions. The comparative results indicate that under flight conditions with significant illumination variations, especially in image stitching areas or areas with large differences in shooting time, radiometric consistency is poor. After processing using the method of this invention, the reflectance distribution within and between field plots becomes more uniform and stable, significantly reducing the systematic bias caused by illumination variations and improving the spatial consistency and temporal comparability of the reflectance results.

[0084] As can be seen, compared with the conventional PanelCal method, the present invention has stronger adaptability and stability under complex and changing lighting conditions. It can obtain more accurate and more consistent UAV image reflectance results without adding extra ground calibration operations, and is particularly suitable for application scenarios such as refined remote sensing monitoring of farmland communities.

[0085] Example 3

[0086] This embodiment verifies the proposed assumption based on a constant ratio.

[0087] First, assume that the ratio of the irradiance of ground features to that of the Lambert plate is a fixed value across different spectral bands.

[0088] Then, global horizontal irradiance (GHI) data for Saihanba were collected throughout the day (including 9:00 and other times) from August to September 2022, and data for the corresponding five bands were selected according to the Altum-PT wavelength parameters.

[0089] Finally, assuming the GHI measurement at 9:00... For the Lambert plate in the band GHI at other times, GHI measurements For ground features in the band GHI. For each band Calculate the ratio of the ground feature GHI to the Lambertian plate GHI at each time point. If different bands If they are approximately equal, then the new hypothesis is supported.

[0090] Figures 4 to 6 show the radiation calibration coefficients under three weather conditions. The value changes over time. The results show that different bands... They are approximately equal and are unaffected by weather type or time.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for radiometric consistency correction of UAV images under varying illumination conditions, characterized in that, include: The process involves: acquiring orthophotos of the target farmland area; performing spatial positioning correction on the orthophotos of the target farmland area and obtaining the spatial location of each farmland plot or experimental plot within the orthophotos; cropping the orthophotos based on the spatial location of each farmland plot or experimental plot within the orthophotos, and performing radiometric consistency correction on the radiometric information in the cropped image affected by changes in illumination based on a constant ratio assumption; and conducting crop growth monitoring, crop condition assessment, variety comparison analysis, or yield prediction based on the radiometric consistency-corrected image data. The process includes cropping the orthophotos based on the spatial location of each farmland plot or experimental plot within the orthophotos and performing radiometric consistency correction on the radiometric information in the cropped image affected by changes in illumination based on a constant ratio assumption. The image is cropped to obtain cropped silhouette images corresponding to each farmland plot or test plot. Based on the assumption of a constant ratio, the radiation information in the cropped silhouette images affected by changes in illumination is subjected to radiation consistency correction processing. This radiation consistency correction processing, based on the assumption of a constant ratio, includes: calculating the irradiance ratio constant coefficient based on the cropped silhouette images of each farmland plot or test plot; calculating the absolute reflectance of the target object based on the irradiance ratio constant coefficient; and normalizing the absolute reflectance of the target object to obtain its relative reflectance. The formula for calculating the irradiance ratio constant coefficient based on the cropped silhouette images of each farmland plot or test plot is as follows: In the formula, Indicates the radiation calibration factor; 、 These represent the center wavelengths of different wavebands; and Indicates the calibration plate at wavelength and wavelength The amount of radiation at that location; and These represent the target ground features at wavelengths of [wavelength values ​​missing]. and wavelength The amount of radiation at that location.

2. The method for radiometric consistency correction of UAV images under varying illumination conditions as described in claim 1, characterized in that, The acquisition of orthophotos of the target farmland area includes: using a drone equipped with a multispectral or visible light sensor to take aerial images of the target farmland area under natural lighting conditions; and performing image stitching processing on the acquired drone images to generate an orthophoto covering the target farmland area.

3. The method for radiometric consistency correction of UAV images under varying illumination conditions as described in claim 1, characterized in that, The step of performing spatial positioning correction on the orthophoto of the target farmland area and obtaining the spatial position of each farmland plot or test plot in the orthophoto in the target farmland area includes: combining real-time dynamic differential positioning technology to perform spatial positioning correction on the orthophoto of the target farmland area to obtain accurate geographic coordinate information of each pixel in the orthophoto; based on the accurate geographic coordinate information of each pixel, using the pre-acquired vector boundary coordinates of each farmland plot or test plot, determining the spatial position of each farmland plot or test plot in the orthophoto.

4. The method for radiometric consistency correction of UAV images under varying illumination conditions as described in claim 1, characterized in that, The formula for calculating the absolute reflectance of the target feature is: In the formula, Indicates the target ground object at wavelength Absolute reflectance at that location; Indicates the target ground object at wavelength Radiance at that location; Indicates the target ground object at wavelength The amount of radiation at that location; Indicates the calibration plate at wavelength Radiance at that location; Indicates the calibration plate at wavelength The amount of radiation at that location; Indicates the calibration plate at wavelength The known reflectivity at that location; This represents the radiation calibration coefficient.

5. The method for radiometric consistency correction of UAV images under varying illumination conditions as described in claim 1, characterized in that, The formula for calculating the relative reflectance of the target feature is: In the formula: Indicates the target ground object at wavelength Relative reflectance at that location; Indicates the target ground object at wavelength Absolute reflectance at that location; Indicates the normalized baseline value; Indicates the target ground object at wavelength Radiance at that location; Indicates the calibration plate at wavelength Radiance at that location, This represents the cross-band normalization term.

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